simpler fix to interpret issue

predicators/datasets/generate_atom_trajs_with_vlm.py

@@ -869,22 +869,12 @@ def _create_prompt_from_image_option_traj(
     for i, a in enumerate(image_option_traj.actions):
         state = image_option_traj.states[i]
         demo_str.append(f"state {i}:")
-        # NOTE: it's important to set the round_feat_vals argument to False
-        # here. If we set it to True, then the VLM might mistakenly propose
-        # predicates that work given rounding, but fail otherwise.
-        # So for instance, a predicate classifier that does `== 0` would
-        # work for a value 0.00123 rounded to a single decimal place,
-        # but wouldn't actually work when deployed on the number 0.00123!
-        demo_str.append(
-            state.dict_str(indent=2,
-                           object_features=True,
-                           round_feat_vals=False))
+        demo_str.append(state.dict_str(indent=2, object_features=True))
         demo_str.append(f"action {i}: {a.name}")
     num_states = len(image_option_traj.states)
     state = image_option_traj.states[-1]
     demo_str.append(f"state {num_states}:")
-    demo_str.append(
-        state.dict_str(indent=2, object_features=True, round_feat_vals=False))
+    demo_str.append(state.dict_str(indent=2, object_features=True))
     demo_str_ = '\n'.join(demo_str)
     template = template.replace("[DEMO_TRAJECTORY]", demo_str_)
 

predicators/structs.py

@@ -215,20 +215,13 @@ def pretty_str(self) -> str:
         suffix = "\n" + "#" * ll + "\n"
         return prefix + "\n\n".join(table_strs) + suffix
 
-    def dict_str(self,
-                 indent: int = 0,
-                 object_features: bool = True,
-                 round_feat_vals: bool = True) -> str:
+    def dict_str(self, indent: int = 0, object_features: bool = True) -> str:
         """Return a dictionary representation of the state."""
         state_dict = {}
         for obj in self:
             obj_dict = {}
             if obj.type.name == "robot" or object_features:
                 for attribute, value in zip(obj.type.feature_names, self[obj]):
-                    if isinstance(
-                            value,
-                        (float, int, np.float32)) and round_feat_vals:
-                        value = round(float(value), 1)
                     obj_dict[attribute] = value
             obj_name = obj.name
             state_dict[f"{obj_name}:{obj.type.name}"] = obj_dict